collaborators

9 papers

cs.CE2026

OpenPM: Auditable Point-in-Time Evaluation for LLM Portfolio-Management Agents

Xinying Cai, Minghao Guo, Jiahe Liu +7

Large language models are increasingly used to read markets, assess risk, and allocate capital. However, reported results for LLM trading agents can be inflated by look-ahead leaka…

cs.IR2026

Trust or Abstain? A Self-Aware RAG Approach

Xi Zhu, Ziqi Wang, Kai Mei +5

Retrieval-augmented generation (RAG) improves large language models (LLMs) by incorporating external evidence, but it also introduces knowledge conflicts when retrieved contextual…

cs.CL2026

AEL: Agent Evolving Learning for Open-Ended Environments

Wujiang Xu, Jiaojiao Han, Minghao Guo +4

LLM agents increasingly operate in open-ended environments spanning hundreds of sequential episodes, yet they remain largely stateless: each task is solved from scratch without con…

cs.IR2026

RAGRouter-Bench: A Dataset and Benchmark for Adaptive RAG Routing

Ziqi Wang, Xi Zhu, Shuhang Lin +3

Retrieval-augmented generation (RAG) has evolved into a family of paradigms with distinct performance profiles and resource demands, turning paradigm selection into a multi-criteri…

cs.CL2026

Individual Turing Test: A Case Study of LLM-based Simulation Using Longitudinal Personal Data

Minghao Guo, Ziyi Ye, Wujiang Xu +3

Large Language Models (LLMs) have demonstrated remarkable human-like capabilities, yet their ability to replicate a specific individual remains under-explored. This paper presents…

cs.SI2026

From Aggregation to Selection: User-Validated Distributed Social Recommendation

Jingyuan Huang, Dan Luo, Zihe Ye +3

Social recommender systems facilitate social connections by identifying potential friends for users. Each user maintains a local social network centered around themselves, resultin…